Investigation of a real-time EPID-based patient dose monitoring safety system using site-specific control limits

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Abstract

Purpose

The aim of this study is to investigate the performance and limitations of a real-time transit electronic portal imaging device (EPID) dosimetry system for error detection during dynamic intensity modulated radiation therapy (IMRT) treatment delivery. Sites studied are prostate, head and neck (HN), and rectal cancer treatments.

Methods

The system compares measured cumulative transit EPID image frames with predicted cumulative image frames in real-time during treatment using a χ comparison with 4 %, 4 mm criteria. The treatment site-specific thresholds (prostate, HN and rectum IMRT) were determined using initial data collected from 137 patients (274 measured treatment fractions) and a statistical process control methodology. These thresholds were then applied to data from 15 selected patients including 5 prostate, 5 HN, and 5 rectum IMRT treatments for system evaluation and classification of error sources.

Results

Clinical demonstration of real-time transit EPID dosimetry in IMRT was presented. For error simulation, the system could detect gross errors (i.e. wrong patient, wrong plan, wrong gantry angle) immediately after EPID stabilisation; 2 seconds after the start of treatment. The average rate of error detection was 7.0 % (prostate = 5.6 %, HN= 8.7 % and rectum = 6.7 %). The detected errors were classified as either clinical in origin (e.g. patient anatomical changes), or non-clinical in origin (e.g. detection system errors). Classified errors were 3.2 % clinical and 3.9 % non-clinical.

Conclusion

An EPID-based real-time error detection method for treatment verification during dynamic IMRT has been developed and tested for its performance and limitations. The system is able to detect gross errors in real-time, however improvement in system robustness is required to reduce the non-clinical sources of error detection.

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Most cited references 23

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Evaluation of the gamma dose distribution comparison method.

Amanda F. Dempsey, D Low (2003)

The gamma tool was developed to quantitatively compare dose distributions, either measured or calculated. Before computing gamma, the dose and distance scales of the two distributions, referred to as evaluated and reference, are renormalized by dose and distance criteria, respectively. The renormalization allows the dose distribution comparison to be conducted simultaneously along dose and distance axes. The gamma quantity, calculated independently for each reference point, is the minimum distance in the renormalized multidimensional space between the evaluated distribution and the reference point. The gamma quantity degenerates to the dose-difference and distance-to-agreement tests in shallow and very steep dose gradient regions, respectively. Since being introduced, the gamma quantity has been used by investigators to evaluate dose calculation algorithms, and compare dosimetry measurements. This manuscript examines the gamma distribution behavior in two dimensions and evaluates the gamma distribution in the presence of data noise. Noise in the evaluated distribution causes the gamma distribution to be underestimated relative to the no-noise, condition. Noise in the reference distribution adds noise in the gamma distribution in proportion to the normalized dose noise. In typical clinical use, the fraction of points that exceed 3% and 3 mm can be extensive, so we typically use 5% and 2-3 mm in clinical evaluations. For clinical cases, the calculation time is typically 5 minutes for a 1 x 1 mm2 interpolated resolution on an 800 MHz Pentium 4 for a 14.1 x 15.2 cm2 radiographic film.

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Statistical process control for radiotherapy quality assurance.

Julie Boyer, Vance M. Whitaker, Todd Pawlicki (2005)

Every quality assurance process uncovers random and systematic errors. These errors typically consist of many small random errors and a very few number of large errors that dominate the result. Quality assurance practices in radiotherapy do not adequately differentiate between these two sources of error. The ability to separate these types of errors would allow the dominant source(s) of error to be efficiently detected and addressed. In this work, statistical process control is applied to quality assurance in radiotherapy for the purpose of setting action thresholds that differentiate between random and systematic errors. The theoretical development and implementation of process behavior charts are described. We report on a pilot project is which these techniques are applied to daily output and flatness/symmetry quality assurance for a 10 MV photon beam in our department. This clinical case was followed over 52 days. As part of our investigation, we found that action thresholds set using process behavior charts were able to identify systematic changes in our daily quality assurance process. This is in contrast to action thresholds set using the standard deviation, which did not identify the same systematic changes in the process. The process behavior thresholds calculated from a subset of the data detected a 2% change in the process whereas with a standard deviation calculation, no change was detected. Medical physicists must make decisions on quality assurance data as it is acquired. Process behavior charts help decide when to take action and when to acquire more data before making a change in the process.

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Catching errors with in vivo EPID dosimetry.

R Tielenburg, B Mijnheer, M F Montfort … (2010)

The potential for detrimental incidents and the ever increasing complexity of patient treatments emphasize the need for accurate dosimetric verification in radiotherapy. For this reason, all curative treatments are verified, either pretreatment or in vivo, by electronic portal imaging device (EPID) dosimetry in the Radiation Oncology Department of The Netherlands Cancer Institute-Antoni van Leeuwenhoek hospital, Amsterdam, The Netherlands. Since the clinical introduction of the method in January 2005 until August 2009, treatment plans of 4337 patients have been verified. Among these plans, 17 serious errors were detected that led to intervention. Due to their origin, nine of these errors would not have been detected with pretreatment verification. The method is illustrated in detail by the case of a plan transfer error detected in a 5 x 5 Gy intensity-modulated radiotherapy (IMRT) rectum treatment. The EPID reconstructed dose at the isocenter was 6.3% below the planned value. Investigation of the plan transfer chain revealed that due to a network transfer error, the plan was corrupted. 3D analysis of the acquired EPID data revealed serious underdosage of the planning target volume: On average 11.6%, locally up to 20%. This report shows the importance of in vivo (EPID) dosimetry for all treatment plans as well as the ability of the method to assess the dosimetric impact of deviations found.

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Author and article information

Contributors

Todsaporn Fuangrod: Todsaporn.fuangrod@uon.edu.au

Peter B. Greer: Peter.Greer@newcastle.edu.au

Henry C. Woodruff: Henry.woodruff@sydney.edu.au

John Simpson: John.Simpson@calvarymater.org.au

Shashank Bhatia: Shashank.bhatia@calvarymater.org.au

Benjamin Zwan: Benjamin.zwan@health.nsw.gov.au

Timothy A. vanBeek: Timothy.vanbeek@cancercare.mb.ca

Boyd M.C. McCurdy: Boyd.mccurdy@cancercare.mb.ca

Richard H. Middleton: Richard.middleton@newcastle.edu.au

Journal

Journal ID (nlm-ta): Radiat Oncol

Journal ID (iso-abbrev): Radiat Oncol

Title: Radiation Oncology (London, England)

Publisher: BioMed Central (London )

ISSN (Electronic): 1748-717X

Publication date (Electronic): 12 August 2016

Publication date PMC-release: 12 August 2016

Publication date Collection: 2016

Volume: 11

Electronic Location Identifier: 106

Affiliations

[1 ]Faculty of Engineering and Built Environment, School of Electrical Engineering and Computer Science, University of Newcastle, Newcastle, NSW Australia

[2 ]Faculty of Science and IT, School of Mathematical and Physical Sciences, The University of Newcastle, Newcastle, NSW Australia

[3 ]Radiation Physics Laboratory Sydney Medical School, The University of Sydney, Sydney, NSW Australia

[4 ]Calvary Mater Newcastle Hospital, Newcastle, NSW Australia

[5 ]Central Coast Cancer Centre, Gosford, NSW Australia

[6 ]Division of Medical Physics, CancerCare Manitoba, Winnipeg, MB Canada

[7 ]Department of Physics and Astronomy, University of Manitoba, Winnipeg, MB Canada

[8 ]Department of Radiology, University of Manitoba, Winnipeg, MB Canada

Article

Publisher ID: 682

DOI: 10.1186/s13014-016-0682-y

PMC ID: 4983007

PubMed ID: 27520279

SO-VID: 03da50e7-39ce-478b-8d1f-a53d5e3e2c4b

License:

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

History

Date received : 22 December 2015

Date accepted : 5 August 2016

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ScienceOpen disciplines: Oncology & Radiotherapy

Keywords: statistical process control,real-time patient dose monitoring safety system,epid

Data availability:

ScienceOpen disciplines: Oncology & Radiotherapy

Keywords: statistical process control, real-time patient dose monitoring safety system, epid

Investigation of a real-time EPID-based patient dose monitoring safety system using site-specific control limits

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Karger: Oncology

Most cited references 23

Evaluation of the gamma dose distribution comparison method.

Statistical process control for radiotherapy quality assurance.

Catching errors with in vivo EPID dosimetry.

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